a2a-protocols

Agent-to-Agent (A2A) Protocols

Enable agents to discover, communicate, and collaborate across frameworks and systems.

The Interoperability Challenge

Different agent frameworks:

• LangChain/LangGraph
• AutoGen
• CrewAI
• Custom implementations

Problem: They can't talk to each other natively.

Solution: Standard protocols for agent communication.

Protocol Landscape (2026)

Protocol	Purpose	Adoption
MCP (Model Context Protocol)	Tool/resource sharing	High (Anthropic-backed)
A2A (Agent-to-Agent)	Agent coordination	Growing
OpenAI Agents Protocol	Agent invocation	OpenAI ecosystem
Custom REST/gRPC	Point-to-point	Common

MCP Integration

MCP Overview

MCP standardizes how agents access tools and resources:

┌─────────────────┐          ┌─────────────────┐
│     Agent       │          │   MCP Server    │
│  (MCP Client)   │◀────────▶│  (Tools/Data)   │
└─────────────────┘          └─────────────────┘
         │
         │  MCP Protocol
         │  - List tools
         │  - Call tools
         │  - Access resources
         ▼
┌─────────────────┐
│  Another Agent  │
│  (MCP Client)   │
└─────────────────┘

Creating an MCP Server

from mcp.server import Server
from mcp.types import Tool, TextContent

# Create MCP server
server = Server("my-agent-tools")

@server.tool()
async def search_database(query: str) -> str:
    """Search the internal database."""
    results = await db.search(query)
    return json.dumps(results)

@server.tool()
async def send_notification(
    recipient: str,
    message: str
) -> str:
    """Send a notification to a user."""
    await notifications.send(recipient, message)
    return "Notification sent"

# Run server
if __name__ == "__main__":
    server.run()

Connecting Agent to MCP

from mcp import ClientSession, StdioServerParameters
from langchain_mcp import MCPToolkit

async def create_mcp_agent():
    """Create agent with MCP tools."""

    # Connect to MCP server
    server_params = StdioServerParameters(
        command="python",
        args=["mcp_server.py"]
    )

    async with ClientSession(server_params) as session:
        # Get tools from MCP
        toolkit = MCPToolkit(session=session)
        tools = toolkit.get_tools()

        # Create LangChain agent with MCP tools
        agent = create_react_agent(llm, tools)

        return agent